Dataset Information

Catching the Wave: Detecting Strain-Specific SARS-CoV-2 Peptides in Clinical Samples Collected during Infection Waves from Diverse Geographical Locations.

ABSTRACT: The Coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) resulted in a major health crisis worldwide with its continuously emerging new strains, resulting in new viral variants that drive "waves" of infection. PCR or antigen detection assays have been routinely used to detect clinical infections; however, the emergence of these newer strains has presented challenges in detection. One of the alternatives has been to detect and characterize variant-specific peptide sequences from viral proteins using mass spectrometry (MS)-based methods. MS methods can potentially help in both diagnostics and vaccine development by understanding the dynamic changes in the viral proteome associated with specific strains and infection waves. In this study, we developed an accessible, flexible, and shareable bioinformatics workflow that was implemented in the Galaxy Platform to detect variant-specific peptide sequences from MS data derived from the clinical samples. We demonstrated the utility of the workflow by characterizing published clinical data from across the world during various pandemic waves. Our analysis identified six SARS-CoV-2 variant-specific peptides suitable for confident detection by MS in commonly collected clinical samples.

SUBMITTER: Mehta S

PROVIDER: S-EPMC9609567 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Publications

Catching the Wave: Detecting Strain-Specific SARS-CoV-2 Peptides in Clinical Samples Collected during Infection Waves from Diverse Geographical Locations.

Mehta Subina S Carvalho Valdemir M VM Rajczewski Andrew T AT Pible Olivier O Grüning Björn A BA Johnson James E JE Wagner Reid R Armengaud Jean J Griffin Timothy J TJ Jagtap Pratik D PD

Viruses 20221007 10

The Coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) resulted in a major health crisis worldwide with its continuously emerging new strains, resulting in new viral variants that drive "waves" of infection. PCR or antigen detection assays have been routinely used to detect clinical infections; however, the emergence of these newer strains has presented challenges in detection. One of the alternatives has been to detect and cha ...[more]

PMID: 36298760

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Project description:Clostridioides difficile is a pathogen often associated with hospital-acquired infection or antimicrobial-induced disease; however, increasing evidence indicates infections can result from community or environmental sources. Most genomic sequencing of C. difficile has focused on clinical strains, although evidence is growing that C. difficile spores are widespread in soil and water in the environment. In this study, we sequenced 38 genomes collected from soil and water isolates in Flagstaff (AZ, USA) and Slovenia in an effort targeted towards environmental surveillance of C. difficile. At the average nucleotide identity (ANI) level, the genomes were divergent to C. difficile at a threshold consistent with different species. A phylogenetic analysis of these divergent genomes together with Clostridioides genomes available in public repositories confirmed the presence of three previously described, cryptic Clostridioides species and added two additional clades. One of the cryptic species (C-III) was almost entirely composed of Arizona and Slovenia genomes, and contained distinct sub-groups from each region (evidenced by SNP and gene-content differences). A comparative genomics analysis identified multiple unique coding sequences per clade, which can serve as markers for subsequent environmental surveys of these cryptic species. Homologues to the C. difficile toxin genes, tcdA and tcdB, were found in cryptic species genomes, although they were not part of the typical pathogenicity locus observed in C. difficile, and in silico PCR suggested that some would not amplify with widely used PCR diagnostic tests. We also identified gene homologues in the binary toxin cluster, including some present on phage and, for what is believed to be the first time, on a plasmid. All isolates were obtained from environmental samples, so the function and disease potential of these toxin homologues is currently unknown. Enzymatic profiles of a subset of cryptic isolates (n=5) demonstrated differences, suggesting that these isolates contain substantial metabolic diversity. Antimicrobial resistance (AMR) was observed across a subset of isolates (n=4), suggesting that AMR mechanisms are intrinsic to the genus, perhaps originating from a shared environmental origin. This study greatly expands our understanding of the genomic diversity of Clostridioides. These results have implications for C. difficile One Health research, for more sensitive C. difficile diagnostics, as well as for understanding the evolutionary history of C. difficile and the development of pathogenesis.

Dataset Information

Catching the Wave: Detecting Strain-Specific SARS-CoV-2 Peptides in Clinical Samples Collected during Infection Waves from Diverse Geographical Locations.

Publications

Catching the Wave: Detecting Strain-Specific SARS-CoV-2 Peptides in Clinical Samples Collected during Infection Waves from Diverse Geographical Locations.

Similar Datasets

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